Data scientists
Resources for data scientists who want to boost their machine learning models with external data.
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46:39Watch videoWebinar: Find and Use the Data You Need With Augmented Data Discovery
In this on-demand webinar, learn how you can use Explorium for augmented data discovery and connect to the data you need for better business insights.
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Read the blog4 Ways To Know If You’re Using the Right Data Preparation Tools
In this blog post, we look at the key questions you need to ask to make sure you’re using the data preparation tools you really need.
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Read the blogMachine Learning in Retail: Building Smarter Inventory Models
See how machine learning in retail can help you build better inventory management systems.
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How to Improve Your Training Data for Vastly Better Machine Learning
Making your training data better is much easier than you think, and you can use several easy strategies for quick wins.
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Read the blog4 Steps You Must Take to Prepare for Predictive Model Deployment
In this article, we explain how to get ready for predictive model deployment, from preparing data pipelines to retraining ML models.
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Read the blogWhat Is Augmented Data Discovery with Explorium?
With so much data in your own stores, it’s tempting to think you have all you need to start producing great predictive insights. This might be The post What Is Augmented Data Discovery with...
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Read the blogTop Tips for Data Preparation Using Python
Your machine learning model is only as good as the data you feed into it. That makes data preparation (or cleaning, wrangling, cleansing, pre-processing, or any The post Top Tips for Data...
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How to Deploy and Future-Proof Your Models: From Theory to Production
It’s no secret that while most organizations understand the importance of machine learning, most initiatives never make it off the ground. Follow this guide to guarantee you make it to production.
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Read the blogDomain Knowledge in Data Science: Are Your Models Ready for Business?
In this in-depth article, we explain how the right questions will help you get the domain knowledge you need for data science for business.
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Read the blogHow Will Data Privacy Look in The Future?
Data privacy continues to be a major hurdle for risk officers. In this article, we explain how the global increase in data surveillance creates short term opportunities but long term risks.
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Read the blogThe Three Skills You Need to Instill in Your Data Science Team
To succeed in the data science field, you need more than just technical acumen. We reveal the secrets to making your team indispensable.
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Read the blogWhy You Need Data Catalogs, Not Databases
When it comes to external data for machine learning, data catalogs provide a handful of time-saving benefits over databases. Learn more.
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AI is Making BI Obsolete, and Machine Learning is Leading the Way
Why are we still hung up on BI? It’s time to embrace a paradigm that empowers us to make smarter, better predictions using real data with machine learning.
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Read the blogHow to Navigate the New Data Science and Machine Learning Landscape
In this article, we explain how to turn the biggest data science challenges of the moment into business opportunities.
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Read the blogWhy Data Marketplaces Are the Future of the Data Economy
Data marketplaces make the lives of data scientists looking for machine learning datasets much easier. Read how.
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Read the blogHow to Connect to the Data Ecosystem
In this article, we explain where external data comes from, the key challenges, and how to connect and utilize it with data science solutions.
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Read the blogHow Our COVID-19 Signals Give Businesses Better Decision-Making Capabilities
With ML models rendered useless, we built an entirely new set of COVID-19 signals in our platform that let organizations understand their risk derived from the current pandemic.
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19:15Watch videoData Science Salon 2020 - The Next Frontier of Data Science: Automated Feature Generation
Dedy Kredo, Head of Customer Facing Data Science at Explorium, presents about augmented data and feature discovery at Data Science Salon Austin.
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Read the blogData Bias and What it Means for Your Machine Learning Models
Let’s take a look at some of the most prevalent types of bias, the data mistakes that cause them – and how to prevent this from happening in your own models.
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Read the blogWant to Get People Excited About Your Machine Learning Project? Tell Them a Story
Top tips to engage stakeholders at every stage of the data science project life cycle.
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